A practical guide to analysing partially observed data. Collecting, analysing and drawing inferences from data is central to research in the medical and social sciences. Unfortunately, it is rarely possible to collect all the intended data. The literature on inference from the resulting incomplete data is now huge, and continues to grow both as methods are developed for large and complex data structures, and as increasing computer power and suitable software enable researchers to apply these methods. This book focuses on a particular statistical method for analysing and drawing inferences from incomplete data, called Multiple Imputation (MI). MI is attractive because it is both practical and widely applicable. The authors aim is to clarify the issues raised by missing data, describing the rationale for MI, the relationship between the various imputation models and associated algorithms and its application to increasingly complex data structures. Multiple Imputation and its Application: * Discusses the issues raised by the analysis of partially observed data, and the assumptions on which analyses rest. * Presents a practical guide to the issues to consider when analysing incomplete data from both observational studies and randomized trials. * Provides a detailed discussion of the practical use of MI with real-world examples drawn from medical and social statistics. * Explores handling non-linear relationships and interactions with multiple imputation, survival analysis, multilevel multiple imputation, sensitivity analysis via multiple imputation, using non-response weights with multiple imputation and doubly robust multiple imputation. Multiple Imputation and its Application is aimed at quantitative researchers and students in the medical and social sciences with the aim of clarifying the issues raised by the analysis of incomplete data data, outlining the rationale for MI and describing how to consider and address the issues that arise in its application.

This text focuses on areas of public health practice in which the systematic application of epidemiologic methods can have a large and positive impact. It describes how best to apply traditional epidemiologic methods for determining disease etiology to "real-life" problems in public health and health services research. Brownson and Petitti's much-needed book bridges the gap between theoretical epidemiology and public health practice, and covers a number of topics not addressed by other epidemiology texts with a focus on methods. This second edition contains a new chapter on the development and use of systematic reviews and one on epidemiology and the law. Each chapter includes one or more case studies intended to illustrate major points from the chapter and to provide a basis for teaching exercises. All of the chapters are authored by leading experts in the fields of epidemiology and public health, and all are fully revised and updated.
The book is intended for practitioners in epidemiology as well as for students in epidemiology and related disciplines that rely on epidemiologic methods and reasoning. It is a practical and informative book for use in academic institutions, federal agencies which have significant educational missions, state and local public health agencies, and health care organizations. By providing a resource of immense accessibility to several key audiences, this edition of Applied Epidemiology: Theory to Practice further extends the fields ability to make a real difference on behalf of better health for all.

This book constitutes the refereed proceedings of the Third International Symposium on Medical Data Analysis, ISMDA 2002, held in Rome, Italy, in October 2002. The 23 revised full papers presented were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on data mining and decision support systems, medical informatics and modeling, time series analysis, and medical imaging.

Public health officials state that vaccines are safe and effective, but the truth is far more complicated. Vaccination is a serious medical intervention that always carries the potential to injure and cause death as well as to prevent disease. Coercive vaccination policies deprive people of free and informed consent--the hallmark of ethical medicine. Americans are increasingly concerned about vaccine safety and the right to make individual, informed choices together with their healthcare practitioners. "Vaccine Epidemic" focuses on the searing debate surrounding individual and parental vaccination choice in the United States.
Habakus, Holland, and Rosenberg edit and introduce a diverse array of interrelated topics concerning the explosive vaccine controversy, including the ethics of vaccination mandates, corrupting conflicts of interest in the national vaccine program, and personal narratives of parents, children, and soldiers who have suffered vaccine injury.
Newly updated with additional chapters focusing on institutional scientific misconduct, mandates for healthcare workers, concerns about HPV vaccine development, and the story behind the Supreme Court's recent vaccine decision, "Vaccine Epidemi"c remains the essential handbook for the vaccination choice movement and required reading for all people contemplating vaccination for themselves and their children.

Opioids. Concussions. Obesity. Climate change. America is a country of everyday crises - big, long-spanning problems that persist, mostly unregulated, despite their toll on the country's health and vitality. And for every case of government inaction on one of these issues, there is a set of familiar, doubtful refrains: The science is unclear. The data is inconclusive. Regulation is unjustified. It's a slippery slope. Is it? The Triumph of Doubt traces the ascendance of science-for-hire in American life and government, from its origins in the tobacco industry in the 1950s to its current manifestations across government, public policy, and even professional sports. Well-heeled American corporations have long had a financial stake in undermining scientific consensus and manufacturing uncertainty; in The Triumph of Doubt, former Obama and Clinton official David Michaels details how bad science becomes public policy - and where it's happening today. Amid fraught conversations of "alternative facts" and "truth decay," The Triumph of Doubt wields its unprecedented access to shine a light on the machinations and scope of manipulated science in American society. It is an urgent, revelatory work, one that promises to reorient conversations around science and the public good for the foreseeable future.

This book describes stochastic epidemic models and methods for statistically analyzing them. It is aimed at statisticians, biostatisticians, and biomathematicians.

International specialists in Microbiology, Infectious Diseases, Internal Medicine, Cardiology Immunology, Pneumonology, Neurology and Epidemiology gathered to this workshop to discuss and enhance interdisciplinary knowledge on the possible etiological role of Chlamydia pneumoniae, a widespread human respiratory infection, in the pathogenesis of chronic inflammatory diseases with major public health impact such as atherosclerosis, cardiovascular disease, adult-onset asthma bronchiale, chronic obstructive pulmonary diseases, reactive arthritis, morbus Alzheimer and multiple sclerosis. Current deficits and goals in the standardisation of diagnostic tools, basic and applied research, design of epidemiological and monitoring of therapy studies were identified. A special feature of this book is the comprehensive collection of state-of-the-art review articles in the various fields with many references.

This book addresses current topics on pathogenic Vibrio spp. from a comprehensive and holistic perspective. Here, experts in the field provide timely chapters, ranging from genomics, pathogen emergence, and epidemiology to pathogenesis, virulence regulation and host colonization. Questions addressed include: How does climate change affect the spread of these bacteria? What is the status of current vaccines? Are there novel therapeutic options to treat Vibrio infections? Is there likelihood of emergence of new pathogenic strains or species? Can insights from mathematical models and epidemiology lead to prediction of pathogen outbreaks? Recent decades have seen a steady increase in Vibrio spp. infections originating in aquatic and marine habitats, driven by higher human population densities, warming of polluted oceans, natural and human-made disasters, and mass seafood production. These conditions increase the likelihood of pathogenic Vibrio spp. coming into contact with humans, making their study even more timely and relevant as these problems escalate over time. This book is a valuable resource for health management professionals, experienced microbiologists/ microbial ecologists, and early career scientists alike who want to learn more about these important environmental human pathogens. The ideas and technologies presented in this book for preventing, controlling, and monitoring Vibrio spp. infections contribute to the UN Sustainable Development Goal 3: Good Health and Well-Being.

This book covers all details for a successful control and elimination strategy against propagation of deadly liver and intestinal flukes of the genus Schistosoma in China. Cancer due to schistosomiasis is still common in subtropical countries and affords hundred thousands of human and animal deaths per year. Expert authors play close attention to the biology and morphologic aspects of Schistosoma species as well as the history and status quo of schistosomiasis epidemiology. In a unique way, the present work illustrates the need to involve strategic measurements, and to control both adult worms and larval parasite stages. With a special focus on Jiangxi Province, the authors present an effective management plan, ranging from intermediate host snail control to diagnostic tools, medical aid, as well as public health education. This approach from China can be used as blueprint in other countries hit by the same worm infections. The contents of this book will thus be meaningful for academics and practitioners in the fields of parasitology, public health, as well as human and veterinary medicine.

Empirical Likelihood Methods in Biomedicine and Health provides a compendium of nonparametric likelihood statistical techniques in the perspective of health research applications. It includes detailed descriptions of the theoretical underpinnings of recently developed empirical likelihood-based methods. The emphasis throughout is on the application of the methods to the health sciences, with worked examples using real data. Provides a systematic overview of novel empirical likelihood techniques. Presents a good balance of theory, methods, and applications. Features detailed worked examples to illustrate the application of the methods. Includes R code for implementation. The book material is attractive and easily understandable to scientists who are new to the research area and may attract statisticians interested in learning more about advanced nonparametric topics including various modern empirical likelihood methods. The book can be used by graduate students majoring in biostatistics, or in a related field, particularly for those who are interested in nonparametric methods with direct applications in Biomedicine.

Creo que muchos de los profesionales de la salud, no tienen una comprensi n adecuada, acerca de lo que abarca la Medicina del Trabajo y las relaciones que esta tiene con la Epidemiolog a. M s a n, frecuentemente se encuentra una falta de comunicaci n entre el m dico del trabajo y el epidemi logo a pesar de su mutuo inter s en la salud y la enfermedad de los trabajadores. Adem s, considero justo decir, que la mayor a de los estudiantes de medicina y de otras ciencias de la salud, consideran a la Medicina del Trabajo y a la Epidemiolog a, como unidades de aprendizaje aburridas e irrelevantes, las que se estudian nicamente porque se les obliga a ello. Otro punto de vista com n, en lo referente a la Epidemiolog a, es que se le considera altamente matem tica y demasiado compleja para entenderla. Con este pensamiento, he intentado escribir un libro de texto conciso, para m dicos del trabajo, estudiantes de medicina y otros profesionales de la salud, que pueda explicar los conceptos b sicos de la epidemiolog a de manera clara y sencilla. He tratado de suprimir la brecha existente en la comunicaci n entre el M dico del Trabajo como cl nico y el epidemi logo, describiendo algunos ejemplos cl nicos a trav s del libro, explicando al M dico del Trabajo, por que es necesario el nfasis epidemiol gico sobre el estudio de grupos de trabajadores, mas que de individuos.

A one-stop guide for public health students and practitioners learning the applications of classical regression models in epidemiology This book is written for public health professionals and students interested in applying regression models in the field of epidemiology. The academic material is usually covered in public health courses including (i) Applied Regression Analysis, (ii) Advanced Epidemiology, and (iii) Statistical Computing. The book is composed of 13 chapters, including an introduction chapter that covers basic concepts of statistics and probability. Among the topics covered are linear regression model, polynomial regression model, weighted least squares, methods for selecting the best regression equation, and generalized linear models and their applications to different epidemiological study designs. An example is provided in each chapter that applies the theoretical aspects presented in that chapter. In addition, exercises are included and the final chapter is devoted to the solutions of these academic exercises with answers in all of the major statistical software packages, including STATA, SAS, SPSS, and R. It is assumed that readers of this book have a basic course in biostatistics, epidemiology, and introductory calculus. The book will be of interest to anyone looking to understand the statistical fundamentals to support quantitative research in public health. In addition, this book: Is based on the authors course notes from 20 years teaching regression modeling in public health courses Provides exercises at the end of each chapter Contains a solutions chapter with answers in STATA, SAS, SPSS, and R Provides real-world public health applications of the theoretical aspects contained in the chapters Applications of Regression Models in Epidemiology is a reference for graduate students in public health and public health practitioners. ERICK SUAREZ is a Professor of the Department of Biostatistics and Epidemiology at the University of Puerto Rico School of Public Health. He received a Ph.D. degree in Medical Statistics from the London School of Hygiene and Tropical Medicine. He has 29 years of experience teaching biostatistics. CYNTHIA M. PEREZ is a Professor of the Department of Biostatistics and Epidemiology at the University of Puerto Rico School of Public Health. She received an M.S. degree in Statistics and a Ph.D. degree in Epidemiology from Purdue University. She has 22 years of experience teaching epidemiology and biostatistics. ROBERTO RIVERA is an Associate Professor at the College of Business at the University of Puerto Rico at Mayaguez. He received a Ph.D. degree in Statistics from the University of California in Santa Barbara. He has more than five years of experience teaching statistics courses at the undergraduate and graduate levels. MELISSA N. MARTINEZ is an Account Supervisor at Havas Media International. She holds an MPH in Biostatistics from the University of Puerto Rico and an MSBA from the National University in San Diego, California. For the past seven years, she has been performing analyses for the biomedical research and media advertising fields.

Searching for the causes of mental disorders is as exciting as it it complex. The relationship between pathophysiology and its overt manifestations is exceedingly intricate, and often the causes of a disorder are elusive at best. This book is an invaluable resource for anyone trying to track these causes, whether they be clinical researchers, public health practitioners, or psychiatric epidemiologists-in-training. Uniting theory and practice in very clear language, it makes a wonderful contribution to both epidemiologic and psychiatric research. Rather than attempting to review the descriptive epidemiology of mental disorders, this book gives much more dynamic exposition of the thinking and techniques used to establish it.
Starting out by tracing the brief history of psychiatric epidemiology, the book describes the study of risk factors as causes of mental disorders. Subsequent sections discuss approaches to investigation of biologic, genetic, or social causes and the statistical analysis of study results. The book concludes by following some of the problems involved in the search for genetic causes of mental disorders, and more complex casual relationships.

The First Seattle Symposium in Biostatistics: Survival Analysis was held on November 20 and 21, 1995 in honor of the twenty-fifth anniversary of the University of Washington (UW) School of Public Health and Com munity Medicine. This event was sponsored by Amgen and co-sponsored by the UW School of Public Health and Community Medicine and the Division of Public Health Sciences, the Fred Hutchinson Cancer Research Center (FHCRC). The symposium featured keynote lectures by David Cox, Richard Gill and Ross Prentice, as well as invited talks by Norman Bres low, David Clayton, John Crowley, Susan Ellenberg, Mitchell Gail, Nicholas Jewell, Peter Lachenbruch, Jerald Lawless, Kung-Yee Liang, David Oakes, Margaret Pepe, Steven Self, Anastasios Tsiatis, Lee-Jen Wei, Jon Wellner and Zhiliang Ying. It was attended by 437 statisticians from 16 countries. In addition, 163 people attended a two-day short course taught by Thomas Fleming, David Harrington and Terry Therneau on Survival Analysis Meth ods and Software on the weekend preceding the symposium. When the UW School of Public Health and Community Medicine was formed in 1970, biostatistics as a discipline was only a few years old. In the subsequent twenty-five years, both the field and the UW Department of Biostatistics have evolved in many exciting ways. The Department had only seven faculty when it moved from the School of Medicine to the new School of Public Health and Community Medicine in 1970."

COVID-19 has made differential impacts on countries and communities around the world. China, where COVID-19 started, has developed and utilized different types of technologies, including both traditional and disruptive technologies, to address the pandemic risks. Also, there have been many innovations in applying technologies in different contexts during the pandemic as well as in the post-pandemic recovery and preparedness aspects. This book covers some of these technological developments as well as the governance mechanisms for developing a technology and innovation ecosystem in a post-COVID-19 context in China. The book also explores the experiences and lessons learned from different types of technologies and their implementation in the post-COVID-19 period and highlights how they can be useful to prepare for future calamities.

Since the early 2000s, there has been increasing interest within the pharmaceutical industry in the application of Bayesian methods at various stages of the research, development, manufacturing, and health economic evaluation of new health care interventions. In 2010, the first Applied Bayesian Biostatistics conference was held, with the primary objective to stimulate the practical implementation of Bayesian statistics, and to promote the added-value for accelerating the discovery and the delivery of new cures to patients. This book is a synthesis of the conferences and debates, providing an overview of Bayesian methods applied to nearly all stages of research and development, from early discovery to portfolio management. It highlights the value associated with sharing a vision with the regulatory authorities, academia, and pharmaceutical industry, with a view to setting up a common strategy for the appropriate use of Bayesian statistics for the benefit of patients. The book covers: Theory, methods, applications, and computing Bayesian biostatistics for clinical innovative designs Adding value with Real World Evidence Opportunities for rare, orphan diseases, and pediatric development Applied Bayesian biostatistics in manufacturing Decision making and Portfolio management Regulatory perspective and public health policies Statisticians and data scientists involved in the research, development, and approval of new cures will be inspired by the possible applications of Bayesian methods covered in the book. The methods, applications, and computational guidance will enable the reader to apply Bayesian methods in their own pharmaceutical research.

The Vaccine Safety Manual (new, updated 2012 edition) is the worlds most complete guide to immunization risks and protection. It includes pertinent information on every major vaccine: polio, tetanus, MMR, hepatitis A, B, HPV (cervical cancer), Hib, Flu, chickenpox, shingles, rotavirus, pneumococcal, meningococcal, RSV, DTaP, anthrax, smallpox, TB, and more. All of the information, including detailed vaccine safety and efficacy data, is written in an easy-to-understand format, yet includes more than 1,000 scientific citations. More than 100 charts, tables, graphs and illustrations supplement the text. This encyclopedic health manual is an important addition to every family's home library and will be referred to again and again.

Researchers often have difficulties collecting enough data to test their hypotheses, either because target groups are small or hard to access, or because data collection entails prohibitive costs. Such obstacles may result in data sets that are too small for the complexity of the statistical model needed to answer the research question. This unique book provides guidelines and tools for implementing solutions to issues that arise in small sample research. Each chapter illustrates statistical methods that allow researchers to apply the optimal statistical model for their research question when the sample is too small. This essential book will enable social and behavioral science researchers to test their hypotheses even when the statistical model required for answering their research question is too complex for the sample sizes they can collect. The statistical models in the book range from the estimation of a population mean to models with latent variables and nested observations, and solutions include both classical and Bayesian methods. All proposed solutions are described in steps researchers can implement with their own data and are accompanied with annotated syntax in R. The methods described in this book will be useful for researchers across the social and behavioral sciences, ranging from medical sciences and epidemiology to psychology, marketing, and economics.

The basis for much of medical public health practice comes from epidemiological research. This text describes current statistical tools that are used to analyse the association between possible risk factors and the actual risk of disease. Beginning with a broad conceptual framework on the disease process, it describes commonly used techniques for analysing proportions and disease rates. These are then extended to model fitting, and the common threads of logic that bind the two analytic strategies together are revealed. Each chapter provides a descriptive rationale for the method, a worked example using data from a published study, and an exercise that allows the reader to practice the technique. Each chapter also includes an appendix that provides further details on the theoretical underpinnings of the method. Among the topics covered are Mantel-Haenszel methods, rates, survival analysis, logistic regression, and generalised linear models. Methods for incorporating aspects of study design, such as matching, into the analysis are discussed, and guidance is given for determining the power or the sample size requirements of a study. This text will give readers a foundation in applied statistics and the concepts of model fitting to develop skills in the analysis of epidemiological data.

'Clinical epidemiology' is now widely promoted and taught as a 'basic science' of Evidence-Based Medicine, of clinical EBM to be specific. This book, however, is mostly about that which Miettinen takes to be the necessary substitute for this now-so-fashionable subject - namely, Theory of Clinical Medicine together with its subordinate Theory of Clinical Research. The leit motif in all of this is Miettinen's perception of the need, and opportunity, to bring major improvements into clinical medicine in this Information Age, now that theoretical progress has made feasible the development of practice-guiding Expert Systems for it. Parts of this text constitute essential reading for whoever is expected, or otherwise inclined, to study - or teach - 'clinical epidemiology,' and the same is true of those who set policy for the education of future clinicians; but practically all of it is essential reading for future - and current - academics in the various disciplines of clinical medicine. After all, the text is the result of a concentrated effort, over a half-century no less, to really understand both clinical and community medicine and the research to advance the knowledge-base of these. Research epidemiologists, too, will find this text interesting and instructive.

The second edition of this popular textbook provides an introduction to the principles and methods of epidemiology. Since publication of the first edition in 1993, Basic epidemiology has become a standard reference for education, training and research in the field of public health and has been translated into more than 25 languages. It is used widely, for training public health and environment professionals, undergraduate medical students, and students in other health professions. The second edition provides updated examples of how and why the basics of epidemiology are essential to anyone who is required to understand and apply the principles of disease causation and prevention. The book has a particular emphasis on modifiable environmental factors and encourages the application of epidemiology to the prevention of disease and the promotion of health, including environmental and occupational health. It prepares members of the health-related professions to respond to the need for health services to address all aspects of the health of populations, and to ensure that health resources are used to the best possible effect. It shows how good clinical practice is informed by clinical epidemiology; and its lively, concise style is designed to stimulate a continuing interest in the subject. This edition includes comprehensive chapters on the nature and uses of epidemiology; the epidemiological approach to defining and measuring the occurrence of health-related states in populations; the strengths and limitations of epidemiological study designs, causation, the contribution of epidemiology to the prevention of disease, the promotion of health and the development of health policy, and the role of epidemiology in evaluating the effectiveness and efficiency of health care. It enables students to describe the common causes of death, disease and disability in her or his community; outline appropriate study designs to answer specific questions concerning disease causation, natural history, prognosis, prevention, and the evaluation of therapy and other interventions to control disease, and critically evaluate the literature.

This publication provides guidance on preparing data to be input into an international computerised database for clinical case histories of persons accidentally exposed to whole body irradiation. The publication has resulted from a close collaboration between the Institute of Biophysics including its Hospital Number 6 in Moscow, Russia, and the Institute of Occupational and Social Medicine at the University of Ulm. In both institutions, much experience has been accumulated during the last 20 years in dealing with basic and clinical research in the field of radiation accident management. In both institutions many case histories of radiation accident victims have been recorded. On this basis the scientists and clinicians from both institutions developed, over the last two years, a pre computer proforma to feed the International Computer Database for Radiation Exposure Case Histories, with standardised data from clinical case histories of radiation accident victims. This activity should be seen as part of WHO efforts to establish a network of institutions around the world, competent in Radiation Emergency Medical Preparedness and Assistance. This network has become known as REMPAN and it is prepared to provide medical advice and assistance when a radiation accident occurs in any country. The Institute of Occupational and Social Medicine, at the University of Ulm, is part of this global network.

Die Pharmakoepidemiologie ist im Bereich der Gesundheitswissenschaften eine der jungsten Disziplinen. Sie verbindet die Wissenschaftsbereiche Pharmakologie, klinische Medizin, Epidemiologie und Biostatistik und ist dadurch zur wissenschaftlichen Basis der Praxis der Arzneimittelsicherheit geworden. Das vorliegende englisch-deutsche Worterbuch enthalt die wichtigsten Termini (ca. 500), Definitionen und Konzepte des epidemiologischen Themenspektrums und richtet sich an alle, die Gesundheitsforschung betreiben oder sich mit ihren Ergebnissen auseinandersetzen. Das Buch will dazu beitragen, den Gebrauch von fachspezifischen Termini im Bereich Pharmakoepidemiologie international zu standardisieren. Zur Definition von Begriffen ist jeweils die Originalliteratur herangezogen worden. Die Fundstelle ist fur jeden Terminus angegeben und soll dem Benutzer so die Moglichkeit geben, sich bei Bedarf auch umfassender mit einem Begriff und seinem Umfeld auseinandersetzen zu konnen.

Recent years have seen an explosion in new kinds of data on infectious diseases, including data on social contacts, whole genome sequences of pathogens, biomarkers for susceptibility to infection, serological panel data, and surveillance data. The Handbook of Infectious Disease Data Analysis provides an overview of many key statistical methods that have been developed in response to such new data streams and the associated ability to address key scientific and epidemiological questions. A unique feature of the Handbook is the wide range of topics covered. Key features Contributors include many leading researchers in the field Divided into four main sections: Basic concepts, Analysis of Outbreak Data, Analysis of Seroprevalence Data, Analysis of Surveillance Data Numerous case studies and examples throughout Provides both introductory material and key reference material

In 1793 a disastrous plague of yellow fever paralyzed Philadelphia, killing thousands of residents and bringing the nation's capital city to a standstill. In this psychological portrait of a city in terror, J. H. Powell presents a penetrating study of human nature revealing itself. Bring Out Your Dead is an absorbing account, form the original sources, of an infamous tragedy that left its mark on all it touched.